A robust tool for discriminative analysis and feature selection in paired samples impacts the identification of the genes essential for reprogramming lung tissue to adenocarcinoma

<p>Abstract</p> <p>Background</p> <p>Lung cancer is the leading cause of cancer deaths in the world. The most common type of lung cancer is lung adenocarcinoma (AC). The genetic mechanisms of the early stages and lung AC progression steps are poorly understood. There is currently no clinically applicable gene test for the early diagnosis and AC aggressiveness. Among the major reasons for the lack of reliable diagnostic biomarkers are the extraordinary heterogeneity of the cancer cells, complex and poorly understudied interactions of the AC cells with adjacent tissue and immune system, gene variation across patient cohorts, measurement variability, small sample sizes and sub-optimal analytical methods. We suggest that gene expression profiling of the primary tumours and adjacent tissues (PT-AT) handled with a rational statistical and bioinformatics strategy of biomarker prediction and validation could provide significant progress in the identification of clinical biomarkers of AC. To minimise sample-to-sample variability, repeated multivariate measurements in the same object (organ or tissue, e.g. PT-AT in lung) across patients should be designed, but prediction and validation on the genome scale with small sample size is a great methodical challenge.</p> <p>Results</p> <p>To analyse PT-AT relationships efficiently in the statistical modelling, we propose an Extreme Class Discrimination (ECD) feature selection method that identifies a sub-set of the most discriminative variables (e.g. expressed genes). Our method consists of a paired Cross-normalization (CN) step followed by a modified sign Wilcoxon test with multivariate adjustment carried out for each variable. Using an Affymetrix U133A microarray paired dataset of 27 AC patients, we reviewed the global reprogramming of the transcriptome in human lung AC tissue versus normal lung tissue, which is associated with about 2,300 genes discriminating the tissues with 100% accuracy. Cluster analysis applied to these genes resulted in four distinct gene groups which we classified as associated with (i) up-regulated genes in the mitotic cell cycle lung AC, (ii) silenced/suppressed gene specific for normal lung tissue, (iii) cell communication and cell motility and (iv) the immune system features. The genes related to mutagenesis, specific lung cancers, early stage of AC development, tumour aggressiveness and metabolic pathway alterations and adaptations of cancer cells are strongly enriched in the AC PT-AT discriminative gene set. Two AC diagnostic biomarkers SPP1 and CENPA were successfully validated on RT-RCR tissue array. ECD method was systematically compared to several alternative methods and proved to be of better performance and as well as it was validated by comparison of the predicted gene set with literature meta-signature.</p> <p>Conclusions</p> <p>We developed a method that identifies and selects highly discriminative variables from high dimensional data spaces of potential biomarkers based on a statistical analysis of paired samples when the number of samples is small. This method provides superior selection in comparison to conventional methods and can be widely used in different applications. Our method revealed at least 23 hundreds patho-biologically essential genes associated with the global transcriptional reprogramming of human lung epithelium cells and lung AC aggressiveness. This gene set includes many previously published AC biomarkers reflecting inherent disease complexity and specifies the mechanisms of carcinogenesis in the lung AC. SPP1, CENPA and many other PT-AT discriminative genes could be considered as the prospective diagnostic and prognostic biomarkers of lung AC.</p

High Mutability of the Tumor Suppressor Genes RASSF1 and RBSP3 (CTDSPL) in Cancer

BACKGROUND:Many different genetic alterations are observed in cancer cells. Individual cancer genes display point mutations such as base changes, insertions and deletions that initiate and promote cancer growth and spread. Somatic hypermutation is a powerful mechanism for generation of different mutations. It was shown previously that somatic hypermutability of proto-oncogenes can induce development of lymphomas. METHODOLOGY/PRINCIPAL FINDINGS:We found an exceptionally high incidence of single-base mutations in the tumor suppressor genes RASSF1 and RBSP3 (CTDSPL) both located in 3p21.3 regions, LUCA and AP20 respectively. These regions contain clusters of tumor suppressor genes involved in multiple cancer types such as lung, kidney, breast, cervical, head and neck, nasopharyngeal, prostate and other carcinomas. Altogether in 144 sequenced RASSF1A clones (exons 1-2), 129 mutations were detected (mutation frequency, MF = 0.23 per 100 bp) and in 98 clones of exons 3-5 we found 146 mutations (MF = 0.29). In 85 sequenced RBSP3 clones, 89 mutations were found (MF = 0.10). The mutations were not cytidine-specific, as would be expected from alterations generated by AID/APOBEC family enzymes, and appeared de novo during cell proliferation. They diminished the ability of corresponding transgenes to suppress cell and tumor growth implying a loss of function. These high levels of somatic mutations were found both in cancer biopsies and cancer cell lines. CONCLUSIONS/SIGNIFICANCE:This is the first report of high frequencies of somatic mutations in RASSF1 and RBSP3 in different cancers suggesting it may underlay the mutator phenotype of cancer. Somatic hypermutations in tumor suppressor genes involved in major human malignancies offer a novel insight in cancer development, progression and spread

Evolution, heterogeneity and global dispersal of cosmopolitan genotype of Dengue virus type 2

10.1038/s41598-021-92783-yScientific Reports1111349

Epstein-Barr Virus Immortalization of Human B-Cells Leads to Stabilization of Hypoxia-Induced Factor 1 Alpha, Congruent with the Warburg Effect

Background: Epstein-Barr virus (EBV) encodes six nuclear transformation-associated proteins that induce extensive changes in cellular gene expression and signaling and induce B-cell transformation. The role of HIF1A in EBV-induced B-cell immortalization has not been previously studied. Methods and Findings: Using Western blotting and Q-PCR, we found that HIF1A protein is stabilized in EBV-transformed lymphoblastoid cells. Western blotting, GST pulldown assays, and immunoprecipitation showed that EBV-encoded nuclear antigens EBNA-5 and EBNA-3 bind to prolylhydroxylases 1 and 2, respectively, thus inhibiting HIF1A hydroxylation and degradation. Immunostaining and Q-PCR showed that the stabilized HIF1A translocates to the nucleus, forms a heterodimer with ARNT, and transactivates several genes involved in aerobic glycolysis. Using biochemical assays and Q-PCR, we also found that lymphoblastoid cells produce high levels of lactate, lactate dehydrogenase and pyruvate. Conclusions: Our data suggest that activation of the aerobic glycolytic pathway, corresponding to the Warburg effect, occurs in EBV-transformed lymphoblastoid cells, in contrast to mitogen-activated B-cells

Sense-antisense gene-pairs in breast cancer and associated pathological pathways

More than 30% of human protein-coding genes form hereditary complex genome architectures composed of sense-antisense (SA) gene pairs (SAGPs) transcribing their RNAs from both strands of a given locus. Such architectures represent important novel components of genome complexity contributing to gene expression deregulation in cancer cells. Therefore, the architectures might be involved in cancer pathways and, in turn, be used for novel drug targets discovery. However, the global roles of SAGPs in cancer pathways has not been studied. Here we investigated SAGPs associated with breast cancer (BC)-related pathways using systems biology, prognostic survival and experimental methods. Gene expression analysis identified 73 BC-relevant SAGPs that are highly correlated in BC. Survival modelling and metadata analysis of the 1161 BC patients allowed us to develop a novel patient prognostic grouping method selecting the 12 survival-significant SAGPs. The qRT-PCR-validated 12-SAGP prognostic signature reproducibly stratified BC patients into low- and high-risk prognostic subgroups. The 1381 SAGP-defined differentially expressed genes common across three studied cohorts were identified. The functional enrichment analysis of these genes revealed the GABPA gene network, including BC-relevant SAGPs, specific gene sets involved in cell cycle, spliceosomal and proteasomal pathways. The co-regulatory function of GABPA in BC cells was supported using siRNA knockdown studies. Thus, we demonstrated SAGPs as the synergistically functional genome architectures interconnected with cancer-related pathways and associated with BC patient clinical outcomes. Taken together, SAGPs represent an important component of genome complexity which can be used to identify novel aspects of coordinated pathological gene networks in cancers.ASTAR (Agency for Sci., Tech. and Research, S’pore)Published versio

Schematic view on the role of HIF1A in EBV-infected B-cell.

<p><b>A</b> – HIF1A is hydroxylated by the PHDs under normoxic conditions. The hydroxylated HIF1A is recognized by the VHL, E3 ubiquitin ligase, and HIF1A is degraded on proteasomes in activated B-cells. <b>B –</b> Upon EBV infection, EBNA-3 and EBNA-5 bind to PHD2 and PHD1, respectively, and inhibit HIF1A hydroxylation and degradation. The stabilized HIF1A translocates to the nucleus, forms a heterodimer with ARNT and transactivates genes such as <i>GLUT1</i>, <i>PDK1</i> and <i>LDHA</i>. This results in conversion of pyruvate to lactate, i.e., aerobic glycolysis.</p

HIF1A is localized to the nucleus and cytoplasm in LCLs, in contrast to mitogen-activated B-cells.

<p><b>A –</b> Western blotting of cellular subfractions. The membrane was probed with mouse anti-HIF1A and anti-actin antibodies (left panel). Nuclear HIF1A was detected in the lysates of LCL; however, no nuclear signal for HIF1A was detected in mitogen-activated cells. The HIF1A/actin ratio for all the probes was calculated (right panel). <b>B –</b> Immunostaining of LCLs and mitogen-activated cells with mouse anti-HIF1A antibody (green signal). Nuclear DNA is stained in blue. Notice the presence of nuclear HIF1A signal in LCL (panels <b>a</b> and <b>b</b>) and its absence in the mitogen-activated cells (<b>c</b> and <b>d</b>).</p

Expression level of HIF1A in EBV-infected and mitogen-activated B-cells, and in LCLs.

<p><b>A –</b> Western blotting of HIF1A and its hydroxylated form in LCLs (left panel). The membrane was probed with mouse antibody against HIF1A and the rabbit serum against the hydroxylated form of HIF1A (HIF1A-OH). Notice the absence of HIF1A-OH in LCLs (first lane) and the lack of effect of proteasome inhibition. In contrast, high levels of hydroxylated HIF1A were detected in control MCF7 cells upon proteasome inhibition (right panel). <b>B –</b> Western blotting of whole cell lysates of CD40+IL4-activated B-cells, freshly EBV-infected B-cells and LCLs. Cells were treated with 1 mM NiCl₂, mimicking hypoxia-like conditions. Notice that HIF1A, PHD1 and PHD2 levels in LCLs did not change upon treatment with NiCl₂, in contrast to freshly infected cells. <b>C – </b><i>HIF1A</i> expression in CD40+IL4-activated (ABC), freshly EBV-infected (EBC) B-cells and LCLs (LCL) measured by Q-PCR.</p

PHDs 1 and 2 bind to EBNA-5 and EBNA-3, respectively.

<p><b>A –</b> Western blotting following the GST pulldown assay from lymphoblastoid cell lysates. PHD2 and a small portion of PHD1 were precipitated on the beads with GST-EBNA-3 from cell lysate. Positive control shows 15% the crude lysate. <b>B –</b> Western blotting following the GST pulldown assay from LCL lysates. PHD1 was precipitated on the support with immobilized GST-EBNA-5 protein from the lymphoblastoid cell lysate. Positive control shows 15% of the crude lysate.</p